Deploy purpose-built AI advising agents that handle degree audits, at-risk outreach, and course planning at scale — without replacing your advisors or your infrastructure.
Research universities face a structural advising crisis. With student-to-advisor ratios exceeding 500:1, advisors cannot deliver timely, personalized guidance to tens of thousands of students.
Degree audits, course sequencing, and prerequisite checks consume hours of advisor time that should be spent on high-stakes student conversations.
Siloed SIS, LMS, and departmental systems make it nearly impossible to get a unified view of each student — leaving at-risk students invisible until it's too late.
Most research universities operate at 500:1 or higher student-to-advisor ratios, making proactive outreach nearly impossible and reactive advising the norm.
NACADA reports average ratios of 296:1 nationally; research universities often exceed 500:1Advisors spend 30–50% of appointment time manually reviewing degree requirements, transfer credits, and course substitutions instead of coaching students on goals and careers.
Up to 50% of advising time lost to administrative audit tasksWithout continuous monitoring across SIS, LMS, and financial aid systems, at-risk students are often flagged only after they've already stopped attending or failed a course.
6-year graduation rates at research universities average 63% (NCES 2023)Banner, PeopleSoft, Canvas, and Blackboard rarely communicate in real time, forcing advisors to toggle between systems and manually reconcile student data for every appointment.
Advisors use an average of 4–6 disconnected systems per advising sessionFirst-generation, transfer, and underrepresented students are least likely to proactively schedule advising appointments, yet most likely to benefit from early intervention.
First-gen students are 89% more likely to leave without a degree (Pell Institute)An AI agent continuously reconciles completed coursework, transfer credits, and declared requirements against degree plans — surfacing gaps and substitution options before the advising appointment even begins.
The advising agent monitors engagement signals across LMS, SIS, and financial aid data to identify at-risk students early and trigger personalized, timely outreach — automatically.
Students receive AI-guided course recommendations based on their degree progress, academic history, prerequisites, section availability, and declared major or concentration.
A purpose-built MentorAI agent answers advising questions around the clock — covering degree requirements, registration deadlines, add/drop policies, and graduation timelines.
Human advisors receive AI-generated student summaries, risk flags, and recommended talking points before each appointment — so every session is informed, efficient, and high-impact.
Agents connect securely to Banner, PeopleSoft, Canvas, and Blackboard via existing APIs. All data stays on your infrastructure — no third-party data sharing, fully FERPA compliant by design.
Map existing SIS, LMS, and advising workflows. Connect AI agents to Banner or PeopleSoft, Canvas or Blackboard via secure APIs. Define agent roles, data access scopes, and compliance boundaries.
Configure the degree audit agent with your institution's program requirements, transfer equivalency rules, and substitution policies. Train the advising agent on catalog content, policies, and FAQs.
Launch with a pilot cohort — typically one college or student population. Train advisors on the copilot dashboard. Collect feedback, measure deflection rates, and refine agent responses.
Scale deployment across all colleges and student populations. Enable proactive at-risk outreach workflows. Establish continuous improvement cycles using interaction analytics and advisor feedback.
Advisors manually pull transcripts, cross-reference catalogs, and check requirements during appointments — consuming 20–30 minutes per session.
AI agent auto-generates a complete degree audit summary before each appointment, with gaps, substitution options, and recommended next courses highlighted.
At-risk students identified reactively via grade reports or faculty referrals — often weeks after warning signs first appeared.
AI continuously monitors LMS engagement, attendance proxies, and SIS data to trigger personalized outreach within days of early warning signals.
Students wait days for email responses or weeks for appointments; after-hours questions go unanswered until the next business day.
Students get instant, accurate answers 24/7 from a purpose-built advising agent trained on institutional policies, catalog, and degree requirements.
All advising queries — from 'what classes should I take?' to 'I'm thinking of dropping out' — land in the same queue with equal priority.
AI handles routine queries autonomously; complex, high-stakes cases are escalated to human advisors with full context and recommended actions.
Advisors toggle between Banner, Canvas, and departmental spreadsheets to assemble a complete picture of each student before and during appointments.
Advisor copilot dashboard surfaces a unified student profile — academic history, risk flags, financial aid status, and engagement data — in one view.
Deploys the student-facing AI advising agent that handles 24/7 degree audit questions, course selection guidance, and personalized academic planning conversations at scale.
The platform layer that connects AI advising agents to Banner, PeopleSoft, Canvas, and Blackboard — enabling secure, real-time data access and multi-agent orchestration across colleges and departments.
Provides the AI-native learning management layer that surfaces student engagement signals used by the at-risk detection agent, and delivers personalized advising nudges within the student's existing learning environment.
See how ibl.ai deploys AI agents you own and control—on your infrastructure, integrated with your systems.